{"id":"W3195954751","doi":"10.3390/pr9091514","title":"Alts: An Adaptive Load Balanced Task Scheduling Approach for Cloud Computing","year":2021,"lang":"en","type":"article","venue":"Processes","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Taif University","keywords":"Job shop scheduling; Computer science; Distributed computing; Fair-share scheduling; Dynamic priority scheduling; Scheduling (production processes); Rate-monotonic scheduling; Fixed-priority pre-emptive scheduling; Two-level scheduling; Cloud computing; Earliest deadline first scheduling; Round-robin scheduling; Flow shop scheduling; Real-time computing; Mathematical optimization; Computer network; Mathematics; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004239449,0.0001905663,0.0002353802,0.00004807612,0.0003588695,0.0003256764,0.0008119468,0.00005525716,0.000001297795],"category_scores_gemma":[0.000248545,0.0001792296,0.00006418546,0.0006888028,0.00003485945,0.00007720291,0.0004869253,0.0001353456,0.00000549754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005713105,"about_ca_system_score_gemma":0.0003090291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000984219,"about_ca_topic_score_gemma":0.000002868147,"domain_scores_codex":[0.9981694,0.00005657316,0.0002578647,0.000757574,0.0003309776,0.0004276136],"domain_scores_gemma":[0.9985632,0.0001704044,0.0001388971,0.000460918,0.0005589701,0.0001075829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009382975,0.00141833,0.0005167805,0.004314448,0.0002795469,0.00006605857,0.01467141,0.7099276,0.000820907,0.02321514,0.001263417,0.2434126],"study_design_scores_gemma":[0.0005041337,0.0001251639,0.00003505354,0.0000999821,0.00001505872,0.0000192025,0.001037591,0.989795,0.002431889,0.0015092,0.004126328,0.0003014588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02905624,0.002387106,0.9651341,0.0002828404,0.000273901,0.0002237595,0.00000227353,0.0003989275,0.002240885],"genre_scores_gemma":[0.6413052,0.000007502005,0.3577361,0.0003675818,0.0003795844,0.00001173209,0.000008423427,0.00001354165,0.0001703031],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.612249,"threshold_uncertainty_score":0.7308772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02645595706510644,"score_gpt":0.2586747537796179,"score_spread":0.2322187967145115,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}